Making Clinical Trial Data Work Together and Improving Visibility Across Systems Through Real-World Case Studies

  • Exploring why, in fully outsourced clinical trial models, visibility across data systems can be less a technology question than a process one
  • Understanding where data signals can fall through the gaps when multiple CROs and vendors have their own internal processes, review cadences and timelines
  • Case study: a pharmacokinetic protocol deviation that never reached the sponsor because it fell between chairs in the communication chain
  • Case study: a screen failure cleaning exercise where a site misinterpretation of instructions led to an irreconcilable discrepancy
  • Exploring how stronger oversight frameworks and clearer agreement on what is expected, and from whom, could prevent these issues
  • Asking what we should be considering before adopting a new digital tool – recognising that a tool can integrate systems, but not always processes

From Patient Experience to Digital Measures: Capturing What Matters and Keys to Successful Implementation in Clinical Trials

  • How patient centered digital measures can capture meaningful changes in health and daily life that traditional, episodic clinical assessments may miss
  • How continuous, real-world wearable data can help assess whether improvements during standardized in-clinic tests translate into meaningful changes in patients’ daily live
  • Real world case examples demonstrating how fit for purpose digital measures can reveal treatment signals, functional changes, and patient relevant outcomes that standard approaches may not fully capture
  • Why successful patient-centered digital measurement requires thoughtful study design, fit-for-purpose algorithms, continuous compliance monitoring, and high-quality data
  • Practical guidance for advancing digital measures from exploratory use toward clinically meaningful endpoints while maintaining patient relevance throughout clinical development

From Study Design to Operational Reality: Making Trials Work at Conception

  • Exploring why protocol amendments, slow enrolment and late feasibility surprises are often failures of execution rather than science
  • Applying real-world operational evidence to trial design decisions before problems surface
  • Identifying execution risks early to design more predictable, scalable trials
  • Including a live demonstration of Aika, Biorce’s AI-driven clinical trials assistant

Trial Data in 2027: The Consent and Governance Layer Pharma Can’t Outsource to a CRO

  • What changes for sponsors when EHDS, eIDAS 2.0 wallets, the Data Governance Act and the AI Act converge on clinical trial data infrastructure.
  • Why current consent and audit-trail architectures will not survive a participant’s right to revoke or port their data, and what the Nordic region is already building as the working answer: consent evidence ledgers, privacy-preserving computation, and neutral data altruism intermediaries